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Saha A, Govil D, Muhammad T, Thomas AR. Unveiling the dynamics of social engagement and subjective health in older adults: A gendered perspective. Exp Gerontol 2024; 193:112472. [PMID: 38821323 DOI: 10.1016/j.exger.2024.112472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 05/23/2024] [Accepted: 05/24/2024] [Indexed: 06/02/2024]
Abstract
OBJECTIVES As populations age globally, understanding the dynamics that influence the well-being of older individuals become increasingly crucial. The research employs a comprehensive approach to unravel the multifaceted interplay between social engagements and subjective health perceptions of older Indians, with a special focus on gender differences. SUBJECTS AND METHODS This study used data from the Longitudinal Aging Study in India (LASI) wave 1, 2017-18 with a total sample of 30,533 older adults aged 60 years and above. Bivariate analysis, chi-square tests and unadjusted and adjusted average marginal effects from logistic regression models were used to assess the relationship between social engagements and subjective health among older adults, stratified by gender. RESULTS The prevalence of poor health status decreased with higher frequency of social networks among both men (pp. (percentage point) = 6.1; CI (Confidence Interval): 10.6, 1.6) and women (pp. = 9.2; CI: 14.9, 3.4). The adjusted average marginal effects demonstrate that with an increase in the overall score of social engagement, the likelihood of poor health is almost reduced by half. For men, the prevalence of poor health was 9.8 pp. (95 % CI: 13.7, 5.8), while for women, it was 9.3 pp. (95 % CI: 15.2, 3.1). CONCLUSION Gendered perspectives unveil unique patterns, highlighting how societal expectations and roles assigned to each gender may influence the subjective health perceptions of older individuals. This study adds to the expanding knowledge base to enhance the well-being and fulfillment of aging populations, considering the complex interplay of social dynamics and gendered perspectives.
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Affiliation(s)
- Amiya Saha
- Department of Family & Generations, International Institute for Population Sciences, Mumbai, - 400088, India.
| | - Dipti Govil
- Department of Family & Generations, International Institute for Population Sciences, Mumbai, - 400088, India
| | - T Muhammad
- Department of Human Development and Family Studies, The Pennsylvania State University, PA- 16802, USA
| | - Arya Rachel Thomas
- School of Humanities and Social Sciences, Indian Institute of Technology, Madras, India
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Collonnaz M, Minary L, Riglea T, Kalubi J, O'Loughlin J, Kestens Y, Agrinier N. Lack of consistency in measurement methods and semantics used for network measures in adolescent health behaviour studies using social network analysis: a systematic review. J Epidemiol Community Health 2024; 78:303-310. [PMID: 38290822 DOI: 10.1136/jech-2023-220980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 01/21/2024] [Indexed: 02/01/2024]
Abstract
BACKGROUND Social network analysis (SNA) is often used to examine how social relationships influence adolescent health behaviours, but no study has documented the range of network measures used to do so. We aimed to identify network measures used in studies on adolescent health behaviours. METHODS We conducted a systematic review to identify network measures in studies investigating adolescent health behaviours with SNA. Measures were grouped into eight categories based on network concepts commonly described in the literature: popularity, position within the network, network density, similarity, nature of relationships, peer behaviours, social norms, and selection and influence mechanisms. Different subcategories were further identified. We detailed all distinct measures and the labels used to name them in included articles. RESULTS Out of 6686 articles screened, 201 were included. The categories most frequently investigated were peer behaviours (n=201, 100%), position within the network (n=144, 71.6%) and popularity (n=110, 54.7%). The number of measurement methods varied from 1 for 'similarity on popularity' (within the 'similarity' category) to 28 for the 'characterisation of the relationship between the respondent and nominated peers' (within the 'nature of the relationships' category). Using the examples of 'social isolation', 'group membership', 'individuals in a central position' (within the 'position within the network' category) and 'nominations of influential peers' (sub within the 'popularity' category), we illustrated the inconsistent reporting and heterogeneity in measurement methods and semantics. CONCLUSION Robust methodological recommendations are needed to harmonise network measures in order to facilitate comparison across studies and optimise public health intervention based on SNA.
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Affiliation(s)
| | | | - Teodora Riglea
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, Quebec, Canada
- École de Santé Publique de l'Université de Montréal, Département de médecine sociale et préventive, Montréal, Quebec, Canada
| | - Jodi Kalubi
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, Quebec, Canada
- École de Santé Publique de l'Université de Montréal, Département de médecine sociale et préventive, Montréal, Quebec, Canada
- Centre de recherche en santé publique (CReSP), Université de Montréal & CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Université de Montréal, Montréal, Quebec, Canada
| | - Jennifer O'Loughlin
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, Quebec, Canada
- École de Santé Publique de l'Université de Montréal, Département de médecine sociale et préventive, Montréal, Quebec, Canada
| | - Yan Kestens
- École de Santé Publique de l'Université de Montréal, Département de médecine sociale et préventive, Montréal, Quebec, Canada
- Centre de Recherche en Santé Publique (CReSP), Université de Montréal (UdeM), Montréal, Québec, QC, Canada
| | - Nelly Agrinier
- Université de Lorraine, Inserm, INSPIIRE, Nancy, France
- CHRU-Nancy, INSERM, Université de Lorraine, CIC-EC, Epidémiologie Clinique, Nancy, France
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Sánchez-Franco S, Montgomery SC, Torres-Narvaez ES, Ramírez AM, Murray JM, Tate C, Llorente B, Bauld L, Hunter RF, Kee F, Sarmiento OL. How Do Adolescent Smoking Prevention Interventions Work in Different Contextual Settings? A Qualitative Comparative Study Between the UK and Colombia. Int J Behav Med 2023:10.1007/s12529-023-10211-z. [PMID: 37697141 DOI: 10.1007/s12529-023-10211-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/31/2023] [Indexed: 09/13/2023]
Abstract
BACKGROUND Adolescent smoking is associated with significant health and social risks. Previous research has demonstrated the effectiveness of interventions based on behavior change theories in preventing adolescent smoking uptake. However, evidence from the theory-based perspective of evaluation is limited, especially for how such complex interventions work, and how they work when implemented in different contextual settings. METHOD A comparative qualitative analysis was conducted to explore various influences on behavior change among participants taking part in two smoking prevention interventions in Northern Ireland and Bogotá. Twenty-seven focus groups were conducted in 12 schools (6 in Northern Ireland and 6 in Bogota, n = 195 pupils participated; aged 11-15 years). The Theoretical Domains Framework guided a content analysis of the data. RESULTS We found similarities across settings in terms of knowledge, skills, and beliefs related to smoking or vaping behavior change, as well as differences in contextual resources and social influence. Different environmental resources included availability to purchase tobacco products in the neighborhoods and previous information about tobacco risk. Participants in both interventions perceived behavioral change outcomes related to personal skills and intention to not smoke or vape. CONCLUSION These findings have highlighted how both individual factors and contextual resources influence behavior change for smoking prevention in practice. Local contextual factors and social influences affecting pupils should be taken into account in the implementation and evaluation of health behavior change interventions. In particular, this study supports using social and contextual influence strategies in interventions to reduce the onset of adolescent smoking and vaping.
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Affiliation(s)
- Sharon Sánchez-Franco
- School of Medicine, Universidad de los Andes, Carrera 1 # 18A-10 Block Q, 111711018, Bogotá, Colombia
| | | | - Erika S Torres-Narvaez
- School of Medicine, Universidad de los Andes, Carrera 1 # 18A-10 Block Q, 111711018, Bogotá, Colombia
| | - Ana M Ramírez
- School of Medicine, Universidad de los Andes, Carrera 1 # 18A-10 Block Q, 111711018, Bogotá, Colombia
| | - Jennifer M Murray
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Christopher Tate
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK
| | | | - Linda Bauld
- College of Medicine and Veterinary Medicine, Usher Institute and SPECTRUM Consortium, University of Edinburgh, Edinburgh, Scotland, UK
| | - Ruth F Hunter
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Frank Kee
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Olga L Sarmiento
- School of Medicine, Universidad de los Andes, Carrera 1 # 18A-10 Block Q, 111711018, Bogotá, Colombia.
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